Abstract: Multiple chromosomal aberrations, nucleotide substitutions, and epigenetic modifications may occur in human cancer cells, which drive malignant transformation. The Cancer Genome Atlas (TCGA) project aims to promote large-scale multi-dimensional analysis of these molecular characteristics in human cancer and rapidly provide data to researchers. In this study, we introduce four flow paths of the production of TCGA data, the collections of various cancer types, the data category and level, and the standardized pipeline of data analysis, as well as several existing data analytical tools. We used ovarian cancer as an example to introduce the application of the TCGA data in the analyses of mutation, copy number, analysis, and expression. We summarized the important findings of glioblastoma by TCGA teams.